MétaCan
Menu
Back to cohort
Record W1980908219 · doi:10.3390/computation1010016

Structural Features That Stabilize ZnO Clusters: An Electronic Structure Approach

2013· article· en· W1980908219 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComputation · 2013
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMitacsCompute Canada
KeywordsWurtzite crystal structureDensity functional theoryFormalism (music)Materials scienceBand gapElectronic structurePeriodic boundary conditionsNanocrystalStructural stabilityKinetic energyChemical physicsNanotechnologyCondensed matter physicsMolecular physicsBoundary value problemComputational chemistryOptoelectronicsChemistryZincPhysicsClassical mechanicsStructural engineeringQuantum mechanics

Abstract

fetched live from OpenAlex

We show that a simple approach to building small computationally inexpensive clusters offers insights on specific structural motifs that stabilize the electronic structure of ZnO. All-electron calculations on ZniOi needle (i = 6, 9, 12, 15, and 18) and plate (i = 9 and 18) clusters within the density functional theory (DFT) formalism show a higher stability for ZnO needles that increases with length. Puckering of the rings to achieve a more wurtzite-like structure destabilizes the needles, although this destabilization is reduced by going to infinite needles (calculated using periodic boundary conditions). Calculations of density of states (DOS) curves and band gaps for finite clusters and infinite needles highlight opportunities for band-gap tuning through kinetic control of nanocrystal growth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.246
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it